Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F18%3A00106924" target="_blank" >RIV/00216224:14110/18:00106924 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/65269705:_____/18:00068912

Výsledek na webu

<a href="http://dx.doi.org/10.1002/jmri.26166" target="_blank" >http://dx.doi.org/10.1002/jmri.26166</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/jmri.26166" target="_blank" >10.1002/jmri.26166</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter

Popis výsledku v původním jazyce

BackgroundPurposeSegmentation of the gray and white matter (GM, WM) of the human spinal cord in MRI images as well as the analysis of spinal cord diffusivity are challenging. When appropriately segmented, diffusion tensor imaging (DTI) of the spinal cord might be beneficial in the diagnosis and prognosis of several diseases. To evaluate the applicability of a semiautomatic algorithm provided by ITK-SNAP in classification mode (CLASS) for segmenting cervical spinal cord GM, WM in MRI images and analyzing DTI parameters. Study TypeSubjectsProspective. Twenty healthy volunteers. SequencesAssessment1.5T, turbo spin echo, fast field echo, single-shot echo planar imaging. Three raters segmented the tissues by manual, CLASS, and atlas-based methods (Spinal Cord Toolbox, SCT) on T-2-weighted and DTI images. Masks were quantified by similarity and distance metrics, then analyzed for repeatability and mutual comparability. Masks created over T-2 images were registered into diffusion space and fractional anisotropy (FA) values were statistically evaluated for dependency on method, rater, or tissue. Statistical TestsResultst-test, analysis of variance (ANOVA), coefficient of variation, Dice coefficient, Hausdorff distance. CLASS segmentation reached better agreement with manual segmentation than did SCT (P&lt;0.001). Intra- and interobserver repeatability of SCT was better for GM and WM (both P&lt;0.001) but comparable with CLASS in entire spinal cord segmentation (P=0.17 and P=0.07, respectively). While FA values of whole spinal cord were not influenced by choice of segmentation method, both semiautomatic methods yielded lower FA values (P&lt;0.005) for GM than did the manual technique (mean differences 0.02 and 0.04 for SCT and CLASS, respectively). Repeatability of FA values for all methods was sufficient, with mostly less than 2% variance.

Název v anglickém jazyce

Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter

Popis výsledku anglicky

BackgroundPurposeSegmentation of the gray and white matter (GM, WM) of the human spinal cord in MRI images as well as the analysis of spinal cord diffusivity are challenging. When appropriately segmented, diffusion tensor imaging (DTI) of the spinal cord might be beneficial in the diagnosis and prognosis of several diseases. To evaluate the applicability of a semiautomatic algorithm provided by ITK-SNAP in classification mode (CLASS) for segmenting cervical spinal cord GM, WM in MRI images and analyzing DTI parameters. Study TypeSubjectsProspective. Twenty healthy volunteers. SequencesAssessment1.5T, turbo spin echo, fast field echo, single-shot echo planar imaging. Three raters segmented the tissues by manual, CLASS, and atlas-based methods (Spinal Cord Toolbox, SCT) on T-2-weighted and DTI images. Masks were quantified by similarity and distance metrics, then analyzed for repeatability and mutual comparability. Masks created over T-2 images were registered into diffusion space and fractional anisotropy (FA) values were statistically evaluated for dependency on method, rater, or tissue. Statistical TestsResultst-test, analysis of variance (ANOVA), coefficient of variation, Dice coefficient, Hausdorff distance. CLASS segmentation reached better agreement with manual segmentation than did SCT (P&lt;0.001). Intra- and interobserver repeatability of SCT was better for GM and WM (both P&lt;0.001) but comparable with CLASS in entire spinal cord segmentation (P=0.17 and P=0.07, respectively). While FA values of whole spinal cord were not influenced by choice of segmentation method, both semiautomatic methods yielded lower FA values (P&lt;0.005) for GM than did the manual technique (mean differences 0.02 and 0.04 for SCT and CLASS, respectively). Repeatability of FA values for all methods was sufficient, with mostly less than 2% variance.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30224 - Radiology, nuclear medicine and medical imaging

Projekt

<a href="/cs/project/NV15-32133A" target="_blank" >NV15-32133A: Predikce konverze klinicky izolovaného syndromu do roztroušené sklerózy pomocí pokročilých technik zobrazení magnetickou rezonancí</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Magnetic Resonance Imaging

ISSN

1053-1807

e-ISSN

1522-2586

Svazek periodika

48

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

11

Strana od-do

1217-1227

Kód UT WoS článku

000448081300006

EID výsledku v databázi Scopus

2-s2.0-85055211023